{"id":"7b92f57d-2070-4596-aa3b-491c3e6f879f","shortId":"Zf8DNx","kind":"skill","title":"optimize-simplicite-logs","tagline":"capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON.","description":"# Optimize Simplicite Logs\n\nThis skill provides the capability to parse Simplicité logs from a raw `.txt` file, filter fields to reduce noise, and output the result as structured JSON. This is critical for optimizing AI context size (saving ~56% of tokens) and providing structured, predictable data for troubleshooting.\n\n## When to Use This Skill\n\nUse this skill when you need to:\n- Analyze user-provided Simplicité log files in `.txt` format.\n- Avoid ingesting massive raw log files into your context window.\n- Extract structured fields (like `timestamp`, `level`, `body`) from verbose multi-line log output.\n\n**IMPORTANT:** Instead of directly reading a raw `.txt` log file provided by the user using file read tools, you **must** use one of the log converter scripts (PowerShell or Python) to parse the file into a JSON format first, optionally extracting only the fields needed.\n\n## Prerequisites\n\n- Access to either the PowerShell script (`/scripts/SimpliciteLog2Json.ps1`) or the Python script (`/scripts/simplicite-log2json.py`).\n\n## Core Capabilities\n\n### 1. Context Optimization\nReduces the tokens consumed by large Simplicité logs by extracting only relevant log fields (e.g. `body`, `timestamp`, `level`) and discarding non-relevant structural log data (like `app`, `endpoint`, `contextPath`).\n\n### 2. Multi-line Support\nProperly captures stack traces and multiline errors inside the `body` field of the JSON structure, which a simple text search might miss.\n\n### 3. Stdout Support\nIf no output path is provided for the JSON file (e.g. omitting `--output` or `-Output`), the parsed JSON will be printed directly to stdout, allowing you to pipe the output to other tools.\n\n## Output Summary\n\nAfter processing, the tool prints a summary to stderr (or console):\n```\nProcessed: 123 entries, Skipped: 2 entries\n```\n\n## Usage Examples\n\n### Example 1: Python Version (Recommended)\nConvert a log file to JSON, keeping only the most important fields:\n```sh\npython /absolute/path/to/skills/optimize-simplicite-logs/scripts/simplicite-log2json.py <input.txt> --include timestamp,level,body --output <output.json>\n```\n\n### Example 2: PowerShell Version\n```powershell\n/python /absolute/path/to/skills/optimize-simplicite-logs/scripts/SimpliciteLog2Json.ps1 -InputPath \"<input.txt>\" -Output \"<output.json>\" -Include \"body,timestamp,level\"\n```\n\nAfter generating the `<output.json>`, you can safely read the resulting file to perform your analysis.\n\n## Guidelines\n\n1. **Always Convert First:** Never directly read `.txt` log files from Simplicité using standard text reading tools. Always convert them to JSON using the available scripts.\n2. **Filter Fields:** Use `--include` (Python) or `-Include` (PowerShell) to restrict fields to what is absolutely necessary to diagnose the issue (usually `timestamp,level,body`).\n3. **Available Fields:** The fields you can filter include: `timestamp`, `app`, `level`, `endpoint`, `contextPath`, `event`, `user`, `class`, `function`, `rowId`, `body`.\n\n## Common Patterns\n\n### Pattern: Fast Contextual Troubleshooting\n```sh\n# 1. Run the script to generate a minified JSON output in the current directory\npython /absolute/path/to/skills/optimize-simplicite-logs/scripts/simplicite-log2json.py logs.txt --include timestamp,level,body --output logs_minified.json\n\n# 2. Then read logs_minified.json to understand the context.\n```\n\n## Limitations\n\n- The parser depends on a fixed regex pattern that matches the standard Simplicité log output. 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